Non-invasive single cell aptasensing in live cells and animals
Bibliographic record
Abstract
We report a genetically encoded aptamer biosensor platform for non-invasive measurement of drug distribution in cells and animals. We combined the high specificity of aptamer molecular recognition with the easy-to-detect properties of fluorescent proteins. We generated six encoded aptasensors, showcasing the platform versatility. The biosensors display high sensitivity and specificity for detecting their specific drug target over related analogs. We show dose dependent response of biosensor performance reaching saturating drug uptake levels in individual live cells. We designed our platform for integration into animal genomes; thus, we incorporated aptamer biosensors into zebrafish, an important model vertebrate. The biosensors enabled non-invasive drug biodistribution imaging in whole animals across different timepoints. To our knowledge, this is the first example of an aptamer biosensor-expressing transgenic vertebrate that is carried through generations. As such, our encoded platform addresses the need for non-invasive whole animal biosensing ideal for pharmacokinetic-pharmacodynamic analyses that can be expanded to other organisms and to detect diverse molecules of interest.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".